Faculty 교수진 We are the Frontiers of Liberty, Justice and Truth

전임교수

Kihwan Nam
기술경영학과  남기환 조교수 Kihwan Nam
전공분야

Artificial Intelligence [Machine Learning, Computer Vision, NLP (Natural Language Processing)]

Business Analytics & Business Intelligence & Big Data Analytics

Statistical Analysis [Econometrics Models, Predictive Model, Time Series Analysis]

Quantitative Marketing (Econometrics Models for Marketing Decisions)

Stock & Cryptocurrency Price Prediction (Financial Technology)

담당과목

Statistical decision analysis and forecasting, 통계분석 연구방법론

Artificial intelligence business strategy, 인공지능 비즈니스전략

Business Modeling Analysis, 비즈니스 모델링분석

Text Mining, 텍스트 마이닝

학력

B.A., Statistics, Yonsei University

M.S., Industrial Engineering, Korea University

Ph.D., Management Engineering, College of Business, KAIST

경력
Academic Career
  • Assistant Professor, Graduate School of Management of Technology, Korea University
  • Assistant Professor, Information Systems, Business School, Dongguk University
Industry Career
  • Advisor, High Technology-based Artificial Intelligence Company (Robot Field), Aimtory
  • CEO, Artificial Intelligence Solution Company (Healthcare Field), Basbai[Exit]
  • Advisor, Livestock data analysis company, South Korea Livestock Data
연구
Journal Publications
  • Ghose, A., Lee, H., Nam, K., and Oh, W. 2023. "Nudges vs. Sludges: Randomized Field Experiments on the Evaluation of Behavior-Influencing Mechanisms in E Commerce," Forthcoming, Journal of Marketing Research. [Top Journal] UTD24, FT50. [Q1, IF=8.471].
  • Kyeong, N., and Nam, K.* 2022. Mechanism Design for Data Reliability Improvement through Network-Based Reasoning Model, Expert Systems with Applications, 205, 117660. (*Corresponding Author) [Q1, IF=6.954]
  • Lee, D., Nam, K.* Han, I. and Cho, K. 2022. From Free to Fee: Monetizing Digital Content through Utility-based Business Rule Analytics, Information & Management, 59(6), 103681. (*Corresponding Author) [Q1, IF=10.328]
  • Nam, K.* 2022. Conversion Paths of Online Consumers: A Sequential Pattern Mining Approach, Expert Systems with Applications, 202, 117253. (*Corresponding Author) [Q1, IF=6.954]
  • Seong, N., and Nam, K.* 2022. Forecasting Price Movements of Global Financial Indices using Complex Quantitative Financial Networks, Knowledge-Based Systems, 235, 107608. (*Corresponding Author) [Q1, IF=8.139]
  • Nam, K., and Seong, N.* 2021. A Study on Influencing Factors for Customer Satisfaction and the Continuing Use of Social Network Services, Enterprise Information Systems, 15(3), pp. 395-419. [Q1, IF=4.60]
  • Seong, N., and Nam, K.* 2021. Predicting Stock Movements based on Financial News and Market Segmentation, Expert Systems with Applications, 164, 113988. (*Corresponding Author) [Q1, IF=6.954]
  • Im, K., Nam, K.* and Cho, H. 2020. Towards successful business model management with analytic network process-based feasibility evaluation and portfolio management, Electronic Markets, 30, pp. 509~523. (*Corresponding Author) [Q1, IF=6.017]
  • Nam, K., and Seong, N.* 2019. Financial News-based Stock Movement Prediction Using Causality Analysis of Influence, Decision Support Systems, 117, pp. 100-112. [Q1, IF=6.969]
  • Park, J., and Nam, K.* 2019. Group Recommender System for Store Product Placement, Data Mining and Knowledge Discovery, 33(1), pp. 204-229. (*Corresponding Author) [Q1, IF=5.407]
  • Nam, K.*, and Park, M. 2018. Improvement of an Optimal Bus Scheduling Model based on Transit Smart Card Data, Transport, 33(4), pp. 981-992. (*Corresponding Author) [Q2, IF=1.455]
  • Choi, K., and Nam, K.* 2018. Types of Shopping Website Navigation and Purchase Process Pattern Analysis, Journal of Intelligent and Information Systems, 25(1), pp. 85-107. (*Corresponding Author)
  • Shin, H., and Nam, K.* 2018. The Effect of Online Multiple Channel Marketing by Device Type, Information Systems Review, 20(4), pp. 59-78. (*Corresponding Author)
  • Nam, K., and Seong, N.* 2018. Prediction of Block-Buster Drama, Through Initial Viewing-time Pattern Analysis, Journal of Intelligent and Information Systems, 24(4), pp. 33-49.
  • Joe, Y., and Nam, K.* 2017. SKU Recommender System for Retail Stores that Carry Identical Brands using Collaborative Filtering and Hybrid Filtering, Journal of Intelligent and Information Systems, 23(4), pp. 77-110. (*Corresponding Author)
  • Seong, N., and Nam, K.* 2017. Combining macro-economical Effects with Sentiment Analysis for Stock Index Prediction, Entrue Journal of Information Technology, 16(2), pp. 41-54. (*Corresponding Author)

International Conference Proceedings & Presentations
  • Beyond automation: Unpacking the role of trading bots in shaping online cryptocurrency return, with Kanghyun Cho and Jason Thatcher, Academy of Management Proceedings(AOM) 2024.
  • The Effects of Sludges and Nudges on Product Purchases and Returns in Online Retailing: Evidence from a Randomized Field Experiment, with Anindya Ghose, Wonseok Oh, and Heeseung Lee, Workshop on Information Systems and Economics (WISE 2023), Munich, December, 2023.
  • Socialize Less Pay More: The Link Between Virtual Network x-embeddedness and User Contributions, with Kanghyun Cho, Americas Conference on Information Systems (AMCIS), Panama City, Panama, 2023.
  • Who Gets the Money When the Bots Sleep: Investigating the Role of Expertise in the Cryptocurrency Market, with Kanghyun Cho and Jason Thatcher, Statistical Conference in E Commerce Research (SCECR) 2023.
  • The Effects of Sludges and Nudges on Product Purchases and Returns in Online Retailing: Evidence from a Randomized Field Experiment, with Anindya Ghose, Wonseok Oh, and Heeseung Lee, Statistical Conference in E Commerce Research (SCECR) 2023.
  • Designing Recommender Systems in the Presence of Social Influencers, with Angela Choi, and Chad Ho, Conference on Information Systems and Technology(CIST 2022), October, 2022.
  • Bless or Curse: Impact of Algorithmic Trading Bots Invasion on the Cryptocurrency Market, with Kanghyun Cho, International Conference on Information Systems (ICIS) 2022.
  • Bless or Curse: Impact of Algorithmic Trading Bots Invasion on the Cryptocurrency Market, with Kanghyun Cho, Statistical Conference in E-Commerce Research (SCECR) 2022.
  • Neural recommender system considering user homogeneity, with Nohyoon Seong, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) Machine Learning for Consumers and Markets Workshop [KDD] 2021.
  • Deep learning for financial distress prediction considering individual effect and complex system, with Nohyoon Seong, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) Machine Learning in Finance Workshop [KDD] 2021.
  • Better than Humans? AI challenge in Creative Tasks: Randomized Field Experiment on AI Recommender Systems, with Jooyoung Kim, and Nohyoon Seong, 2020 INFORMS Data Science Workshop, November, 2020.
  • Deep learning for financial distress prediction considering individual effect and complex system, with Nohyoon Seong, 2020 INFORMS Data Science Workshop, November, 2020.
  • Predicting stock movements based on financial news with systematic group identification, with Nohyoon Seong, 2020 INFORMS Data Science Workshop, November, 2020.
  • Better than Humans? AI challenge in Creative Tasks: Randomized Field Experiment on AI Recommender Systems, with Jooyoung Kim, and Nohyoon Seong, Conference on Information Systems and Technology(CIST 2020), November, 2020.
  • Straight-up or Made-up? The Impact of Bare-Face Exposure on Cosmetics Sales in Influencer Marketing, with Angela Choi, and Chad Ho, Conference on Information Systems and Technology(CIST 2020), November, 2020.
  • A "Falsely Framed" Choice: A Randomized Field Experiment on the Attraction Effects in Recommender Systems, with Hyelin Oh, Wonseok Oh, and Nohyoon Seong, Conference on Information Systems and Technology(CIST 2020), November, 2020.
  • Context-Dependent Preferences and Image-Based Deep-Learning Recommendations, with Wonseok Oh, and Heeseung Lee, Workshop on Information Systems and Economics (WISE 2019), Munich, December, 2019.
  • The Effects of User Competitions on Sustained Use of M-health Application, with Junetae Kim, and Kanghyun Cho, International Conference on Health Data and Information Services, December, 2019.
  • A "Falsely Framed" Choice: A Randomized Field Experiment on the Attraction Effects in Recommender Systems, with Wonseok Oh, Nohyoon Seong, and Hyelin Oh, Information Systems Review Society, November, 2019. [Best Paper Award].

Published Patents
  • Data Security Maintenance Method for Data Analysis Application”, 10-1978379, Mar. 2019.
  • Apparatus for moving makeup video section through learning”, 10-2020-0098829, August. 2020.
  • Data Security Maintenance Method for Data Analysis Application”, US 11,263,338 B2, Mar. 2022.
  • A method for detecting abnormal motion of a robot arm based on artificial intelligence”, 10-2022-0091561, 2023.
  • Multimodal data processing system and electronic device in smart factory”, 10-2022-0091560, 2023.
  • AI-based robotic arm image data processing method”, 10-2022-0091557, 2023.
  • Apparatus and method for providing a smart factory behavior improvement solution”, 10-2022-0091556, 2023.
  • System for providing safety distance securing service using smart factory-based collaborative robot trajectory analysis”, 10-2023-0030067, 2023.
  • Data synchronization service provision system between vision-based collaborative robots”, 10-2023-0030068, 2023.
  • Mass data processing method and device”, 10-2023-0038798, 2023.
  • Method and apparatus for optimizing robot process having delay compensation function of deadlock point”, 10-2023-0038799, 2023.
  • Method and apparatus for removing vibration noise of robot arm”, 10-2023-0038800, 2023.
  • Motion analysis method and device of humanoid robot based on ergonomics”, 10-2023-0044204, 2023.
  • Robot motion analysis method and apparatus”, 10-2023-0044205, 2023.
  • Noise removal method and device of robot arm”, 10-2023-0040913, 2023.
사회활동

Project

  • Anomaly Detection Model based on Computer Vision Technology, SG Global. [SG Global] (2024)
  • Anomaly Detection Model, Hyundai Heavy Machinary. [현대중공업] (2023)
  • Vibration Data Anomaly Detection and Prediction, HYUNDAI. [현대자동차] (2023)
  • Development of Process Optimization Algorithm, LS ELECTRIC. [LS일렉트릭] (2022)
  • AI Prediction Model Development, SK ecoplant co.,Ltd.. [SK에코플랜트] (2022)
  • Medical Image Analysis, The Catholic University of Korea Catholic Medical Center. [가톨릭대학교의료원] (2022)
  • Temperature Prediction Algorithm, HYUNDAI STEEL. [현대제철] (2022)
  • Medical Image Analysis, Dongguk University Medical Center. [동국대학교의료원] (2021)
  • Medical Image Analysis, Ewha Womans University Medical Center. [이화여대의료원] (2021)
  • Data analysis direction suggestion, Pulmuone. [풀무원] (2021)
  • Development of AI methodology for prediction, KB Financial Group. [KB금융지주] (2020)
  • Data Analysis with R, LG Household & Health care Ltd. [LG생활건강] (2019)
  • Natural Language Processing & Big Data Analysis, AfreecaTV Co., Ltd. [아프리카 TV] (2019)
  • Development of Recommender System, Samsung C&T. [삼성물산] (2017-2019)
  • Recommender System Algorithm, Hyundai Card [현대카드] (2016-2017)
  • Text Mining, Korea Institute of Science Technology Evaluation and Planning. [KISTEP 한국과학기술기획평가원] (2016)
  • Marketing Strategy using Big Data Analysis, AfreecaTV Co., Ltd [아프리카TV] (2016)
  • Customer Marketing Channel Analysis, Adobe Systems Incorporated. [어도비] (2016)
  • Used Car Price Prediction Model, Dong Wha Enterprise Corporation. [동화] (2015)
  • Big Data Analysis, Baedal Eui Minjok. [배달의 민족] (2015)
  • Recommender System using Customer Details Analysis, Samsung Life Insurance Corporation. [삼성생명] (2014)
연구실

인공지능 분야의 테크닉컬한 최신방법론(Computer Vision, Natural Language Processing 등) 및 통계분석방법(Econometrics Models, Predictive Model, Time Series Analysis 등)을 다양한 비즈니스 환경에 적용하여 높은 예측정확도를 기반으로 의미있는 의사결정을 하는 연구 및 인공지능 기술을 적용하면서 새롭게 생겨나거나 상승하는 비즈니스 가치에 대한 연구를 수행한다.

Lab homepage